Speech given at the Society of Technical, Scholarly and Medical Publishers in London on December 7, 2007

1. Using Web 2.0 for OUTSIDE INnovation Patricia Seybold, Founder and CEO, Patricia Seybold Group STM - London December 7, 2007

2. What are the Patterns of Web 2.0? Web 2.0 Social Networking Customer-Contributed Content Executable Web Syndication Published APIs Web Services Really Simple Syndication (RSS) Feeds, Atom Multimedia Photos, Videos, Animation, Audio, Text Rich Internet Apps XML Blogs, Wikis Mash Ups Podcasts Flash, Flex , Ajax Ruby on Rails, Python JavaScript Amazon S3 Google Earth icalendar Gadgets, Widgets Sharing Meta Tags Tagging Linking

3. What are Business Customers Doing?? Organizing Rating Creating Designing Publishing Subscribing Finding Promoting Sharing

5. Guides Contributors Consultants Lead customers Promoters 5 Roles Customers Naturally Play

6. Readers act as Guides By Tagging Scientific and Medical Info

7. www.alexanderstreet.com Stephen Rhind-Tutt, President

8. Playlists

10. Semantic Indexing… Author Birth date Death date Birth Place Death Place Nationality Occupation Awards (38 fields) Theater District Location Capacity Style Etc… (18 fields) Company Name Productions Performers Etc… (14 fields) Production Director Theater Cast # of Perfs. Lighting Costumes Etc… (47 fields) Characters Plays Age Author Performer Etc… (30 fields) Scenes Where When Setting Subject Etc… (41 fields) Resources Play Director Theater Production Co. Character Scene Etc… (45 fields) Texts Keyword Author Date Written Date Published Production (67 fields) Give me scenes about AIDS written by South African authors in the past 5 years….

12. Popularity Effectiveness Folksonomies Taxonomies Taxonomy + Folksonomy

13. When EVERYONE tags, discovery is fun!

14. Everyone is Contributing; Shared Services Make Findability and Re Use Easy

15. Edmunds.com’s Customers Write “How To’s”

16. Customers Create Mash Ups

17. Mozilla is Designed by Users

18. Mozilla is QA’d by Users

19. Mozilla is Supported by Users

20. Mozilla is Promoted by Users

21. 50% of NIs’ New Products Come from Lead Customers 50% of National Instruments’ Products are designed by its Customers and its Ecosystem Customers and Partners Contribute their own Engineering Applications to the Community Lead User Community drives product development Customers Identify and Prioritize all Feature Requests for R&D

22. Next generation games: Co-designed by Lead Customers and Contributors

23. Customers’ Virtual Creations Go Physical

24. Customers create products for others to sell

25. Karmaloop’s Lead Customers: Find and Model Urban Streetwear

26. Karmaloop Community Finds and Reps the Products 10,000 Karmaloop Customers are its Promoters (and its Sales Reps!)

27. Karmaloop’s Lead Customers Strut their Stuff as Designers

30. National Instruments’ Customers have Embraced 2.0

31. Search: Optical Nanotechnology Motion Control

32. Rate & Review Submissions

33. Search: Sound Signal Acquisition

35. Customers use NI’s LabVIEW to Create Courses

36. View Customer Profiles: Find Resources

37. WHAT IS THE TERMINAL VELOCITY OF A SNOWFLAKE? So as I am watching the snow fly horizontally outside my window, it occured to me that that if 1) I knew the terminal velocity of a snow flake 2) Measured the angle the snow's impact vector with the ground 3) and applied a little trig I could estimate the wind’s speed. So does anyone know the terminal velocity of a snow flake? Ben PS Add a vision system and I could automate the measurement.

38. Well you will have to watch out when you use vision pattern recognition...because as everyone knows, every snowflake is unique! although looking out my window at a field of now deep snow...I’m doubting that theory. However I would need a lot more free time before I headed outside to search for two identical snowflakes.... Ben the other way to estimate the wind speed is www.theweathernetwork.com As for your question, I would have to say the terminal velocity would be affected quite heavily by snow consistency and flake size. You might also have to compensate for noisy data, since snowflakes 'tumble' (which would mess with your vector). Furthermore since you are looking out of a building, your results would be effected by the updraft from the wind being deflected by the building. (Just a warning in case your results lead you to believe there is a hurricane in progress and you try to convince your coworkers to take cover).

39. A snowflake vision system would require LV-RT and not be a precise estimate of speed. The feeling of the snow coming to an abrupt stop against you face is a bit more accurate.. How fast your face freezes is another.. Or you could always get one of those turbine thingy that has a speed transducer on it. Your whirly-wind hat with an hall-effect sensor should do the trick! You know the diameter where the sensor is mounted, the rest is simple math. Use a graph to show wind bursts and velocity transitions! Jeff, you could present that project at the next LV User Group meeting!!

40. Ben wrote: 2) Measured the angle the snow's impact vector with the ground Remember that the wind speed is a 3D vector and you're only measuring the projection perpendicular to the view direction. Not to mention the "ground effects". You need to measure the angle away from any surfaces. You could measure the trajectories with two cameras pointing 90° apart and fit the 3D trajectories to a model function that you then can extrapolate to an infinite distance away from the ground. Maybe you should stick to some doppler radar setup.

41. After reading Ben’s post, I had to point out that he was really re-inventing Particle Image Velocimetry (PIV), which I used quite a bit in my Artificial Organs past. The snow already exists as a particle in the fluid of study This link support's Altenbach's requirement for a second camera. http:// darwin.bio.uci.edu/~edrucker/home/dpiv.htm Here is the kind of thing I had done, with hearts and arteries and so on: http:// www.ladhyx.polytechnique.fr/activities/bio_en.html Both of these images are 2D, but 3-D reconstruction is also done, it is just MUCH more processor intensive - No real time results as JoeLabView said! It gets really exciting when you have porous media (imagine the snow blowing through a tightly-packed cornfield...): http:// medschool.umaryland.edu/artificial_organs/pump_comp.asp -Mello

43. Connexions’ Users are Harnessing Web 2.0

45. Staples’ Customers are Leveraging 2.0

46. Staples’ Customers Categorize Products

47. Staples’ Customers Rate & Review Products

49. Dell’s Customers are Driving Web 2.0

53. Dell’s Contributors Add Value thru How To’s

54. Dell Service Tag Widget: Customer-Created

56. National Semiconductor’s Rich Internet Apps

57. WEBENCH ® Flash-based Online Design and Prototyping Environment Select Part Enter Specifications 1. Choose a Part For Power, Amplifiers, Audio, Data Conversion, and RF/Wireless 2. Create a Design Custom Prototype Kit Overnight Prototype 4. Build It! Generate Schematic/ Electrical Analysis Generate Layout/ Thermal Analysis 3. Analyze a Design

58. Customers Use National’s Tools to Design

59. National Semiconductor’s WEBENCH  Toolkit Application Resources System Overview Diagram Layout Sortable Selection Guide WEBENCH Simulation

60. WEBENCH® HotWire Opens Up Any Design HotWire

61. Virtual Designs Save Precious Time Now (Hours) Then (Weeks)

62. Customer Influenced Design Cycle Product Line, 3 rd Parties, WW Design Centers Capture Designs Product Application Design Centers & Field Application Engineers Modify Designs Proposals, App Notes, Reference Designs In Library

78. GuyzNight’s Mash-Up Hits it Big

80. How to Harness Customer Innovation

84. Patty’s Widgets/Gadgets

85. Patricia Seybold CEO, Consultant, and Author [email_address] 617.912.3107 This work is licensed under a Creative Commons License. You may re-use any of these slides or the images on them as long as you attribute them to: 2007 - Patricia Seybold Group, www.psgroup.com Patricia Seybold Group Boston, MA 02129 617.742.5200 www.psgroup.com www.outsideinnovation.blogs.com